Crisis makes inventive!
Crisis makes inventive, that could be the new guiding theme of Qass. We have taken advantage of the prescribed mandatory break to thoroughly refit our products and to break new ground in the process. In absolute consequence, completely new products have been developed, which put the user of the measuring system and the applicability through optimal adaptability in the foreground. In the field of plastic injection moulding, we are proud to present a fundamentally new measuring method that takes the condition monitoring of tools in plastic injection moulding to a new level.
Closed tools have a simple disadvantage. You cannot perceive what is happening inside. However, Qass has a reliable method with structure-borne sound that allows the processes in a mould to be displayed with microsecond accuracy using structure-borne sound, thus enabling each individual process step to be evaluated. The installation of a structure-borne sound sensor is very easy and does not influence the production in any way, because it can be measured inline. The sensor is simply applied to the tool by means of a small hole. The spectral analysis detects even the smallest process irregularities.
Injection moulding tools are usually complex and expensive.
They are subject to wear and contamination depending on the number of shots. Users must therefore carry out regular cleaning and maintenance. The maintenance intervals are based not least on empirical values. For example, mould inspections and maintenance are only carried out if the quality of the parts is inadequate or the moulds fail completely. This is the most expensive maintenance case. Preventive and predictive maintenance is desirable because it increases the reliability of the tools and improves productivity.
QASS tool monitoring
The Qass structure-borne noise sensor is applied directly to the mould and the sensor data is analysed with the Qass Optimizer4D measuring device. The sensor data is subjected to a spectral analysis. This offers the advantage that, in addition to the time-precise representation of the process, various effects such as friction, cracks or abnormal process behaviour can be directly detected. Further advantages are the stability of the measuring process and the accompanying evaluation under harsh environmental conditions in production by using adaptive electronic filters. The mostly occurring creeping changes in the tool are detected by means of a special data analysis.
Data analysis on two levels
The data analysis takes place within two levels. The first level is strictly designed for the analysis and calculation of the data, the second level for visualization and simplified access to the first level. The first level is based on the Qass operator model. An operator is a small program that represents various functions of the instrument or ability to analyze data, as well as the visualization of data. Class 1 provides access to the basic functions of the encoder such as the provision of data or time signals. Class 2 operators are used to perform data analysis. A special feature is the pattern recognition based on the spectral data by searching referenced process sections as objects in new data streams. This allows quick success in process analysis and evaluation and effective identification of disturbance variables. Class 3 is mainly used for machine communication or simple presentation of data. Many processes can already be analyzed with the existing operators and can be specially adapted to the requirements of the process.
General adaptability also for the challenges of tomorrow
Where this adaptability is not sufficient, the user can fall back on further adaptability options. The operators already implemented in the system are programmed in C++. Fast, tailored to the application and reliable. On the other hand rigid and not quickly adaptable. In order to combine the advantages of the implemented operators with the dynamics of scripts, the class of script operators was created. We use the object-oriented Java script for adaptive access to data functions of the operator model and the aspect-oriented Python script to extend the instrument with additional capabilities like machine learning. With the script operators we have designed a special application for the evaluation of the wear condition of tools in plastic injection molding. In the process image, the always same tool movements are represented as sequences of different signals. Each signal sequence can then be assigned to a specific mould movement, e.g. a slide movement, air outlet or cavity filling. Each signal sequence can then be assigned to a specific mould movement, e.g. a slide movement, air outlet or cavity filling. Each sequence is recorded as a data point and written in an overview diagram that records all signals since installation and production readiness. In this way, trends can be quickly recorded and also automatically analysed. In this way, you also have several hundred mould movements reliably under control. Micro-maintenance can then lead to a significant increase in tool life or you can finally get feedback on the optimum maintenance time for your tool.
With Qass, you can also meet the process changes of tomorrow with confidence. We change our way of working to the process adaptation of our users. Due to the new possibilities of the software, we need days instead of months to carry out a specially tailored process adaptation. Additional security is also provided by the possibility of using machine information or signals from other sensors additionally within the framework of a sensor and information fusion. In doing so, the sensors are actively made accessible to the system via the measuring chain or via the existing computer interfaces such as USB, network or BUS communication.